Journal article
High-Speed Defect Detection in Rails by Noncontact Guided Ultrasonic Testing
Transportation research record, v 1916(1916), pp 66-77
01 Jan 2005
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recent train accidents have reaffirmed the need to develop rail defect detection systems that are more effective than those used today. This paper proposes new inspection systems for detecting transverse-type cracks in the rail head, notoriously the most dangerous flaws in rails. In principle these systems can be applied to both continuous welded rail and jointed tracks because bidirectional inspection can be implemented. However, the systems may fail to detect defects located close to a joint. The proposed technology uses ultrasonic guided waves that are detected by remote sensors positioned as far away as 76 mm (3 in.) from the top of the rail head. An impulse hammer is used to generate waves below 50 kHz that can successfully detect cracks larger than 15% of the head cross-sectional area. For smaller crack-those as shallow as 1 mm-a pulsed laser is used for generating waves above 100 kHz. The inspection ranges are at least 10 m (32 ft) for cracks larger than 15% of the head area and at least 500 mm (20 in.) for surface head cracks as shallow as 1 mm. The defect detection reliability is improved by using both reflection and transmission measurements.
Metrics
13 Record Views
Details
- Title
- High-Speed Defect Detection in Rails by Noncontact Guided Ultrasonic Testing
- Creators
- Francesco di ScaleaIvan BartoliPiervincenzo RizzoMahmood FatehTRB
- Publication Details
- Transportation research record, v 1916(1916), pp 66-77
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000236112800010
- Other Identifier
- 991020547317204721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Civil
- Transportation Science & Technology